Date of Award

1-1-2015

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

School of Criminal Justice

Content Description

1 online resource (v, 244 pages) : color illustrations, color maps.

Dissertation/Thesis Chair

Robert E. Worden

Committee Members

Shawn Bushway, Glenn Deane, Colin Loftin, Graeme Newman

Keywords

aggregation-bias, bars, broken-windows, causal-inference, Crime analysis, Geographic information systems, Digital mapping, Small area statistics

Subject Categories

Criminology | Geography | Statistics and Probability

Abstract

The dissertation is aimed at advancing knowledge of the correlates of crime at small geographic units of analysis. I begin by detailing what motivates examining crime at small places, and show how aggregation creates confounds that limit causal inference. Local and spatial effects are confounded when using aggregate units, so when the researcher wishes to distinguish between these two types of effects it should guide what unit of analysis is chosen. To illustrate these differences, I generate simulations of what happens to effect estimates when you aggregate a micro level spatial effects model or presume a neighborhood effects model.

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